A Sectional Refresher

We are hopefully going to be hearing a lot more about sectional timing - more importantly, what sectional timing tells us about how horses performed and races were run - this season and beyond. With that in mind, I thought I'd offer a little refresher... to myself as much as anyone!

I, and Tony Keenan before me, have written about the subject and I'd encourage you to read those articles:

Why Sectionals Matter

What Is The Point of Sectional Timing in Horse Racing

For those who want to get stuck into the mechanics, I highly recommend Simon Rowlands' Introduction to Sectional Timing, which you can download here.

If you favour speaky over reading, the video below is part 'why sectionals' and part 'how it works round here' and includes the answer to the crucial question, "How do I switch it on in my geegeez setup?"

Secure a beverage and give it a peruse if you fancy...

Oh, and any questions, leave a comment below. If I don't know the answer (quite possible), I will try to find someone who does.


5th June Video Preview: Bringing it together

In this fifth and final video preview of the week, I use the racecards, form tools and reports to isolate a few interesting horses in the seven older-horse handicaps taking place on Friday.

This series has been about process rather than desperately trying to pick winners. Happily, it has illustrated the process with numerous scores including 22/1 Zodiakos on the very first day. Whether you backed any of them or not, I hope you've gained some insights into the kit we have here and what it can do for YOU.

Most importantly, I hope you've seen that fun and profit are not mutually exclusive and that winning from betting on horses is possible.

Here's my final episode of the weekend. With luck there will be something of value within...

4th June Preview: 2yo Races, and Laying

In today's video, I cover a few points which have been raised this week, specifically:

- why don't my Report Angles show straight after I've set them up?

- how can I use reports for the purpose of laying horses?

And I gaze through the fog of unraced two-year-old races in the vain hope of trying to find a bet...

3rd June Preview: Gold Trainer Reports

In tonight's video preview of tomorrow's racing, I get all evangelical about one particular component of the Gold setup that you absolutely MUST use. It is golden. It really is. Honestly. Watch the video to see what, and why. And please, please, please take action with it: it will improve your betting literally overnight.

Important Note:

The report jobs run twice daily so anything you configure as per the video will not instantly populate. However, once you've set things up they'll be in place from the next report run onwards. (The reports run at 4.30 am/pm daily, and I'm triggering a few extras at the moment to pick things up a little more in real time).

Here's the video...

Racing is Back! 1st June Video Preview

Racing is back! My, how we've missed it. And, to celebrate its return, as well as the return of plenty of subscribers old and new, I've recorded a video preview of the opening contest.

Regardless of how long you've been a Gold subscriber - perhaps you're still not - I hope you'll find some value in the video, which is designed to highlight a process rather than a tip... though as you'll discover I found a few reasons to like a 20/1 shot!

In the video I refer to a post talking about our metrics, which you can find here.

And here's a quick link to the Newcastle Punting Pointers article.

And, finally, if you're not a Gold subscriber, here's the link to sign up. Get your first month for just £1.


Gold Updates: Cosmetics and PRB

As well as providing bundles of top class thought-provoking editorial during this interminable lockdown, we've also been beavering away on generating some new bells and whistles on our racecards. Actually, we've been mostly cosmetically enhancing our existing features. Let's start with those...

Blue is the new grey

First up, you'll see a lot more blue about the place and a lot less grey.

The card tab now looks like this:


Full Form, with its collapsible blocks, now looks like this:

In the above example, for a geegeez.co.uk syndicate horse, I've collapsed the Race Form and Race Entries blocks.


Your first 30 days for just £1

Perhaps the biggest change is to Instant Expert where we've inverted the colour blocks. So, where previously the outlines and numbers were in the colour (green, amber, red), now the block is that colour with the number font in white. It looks like this:



Similar cosmetic amendments have been made to the result, pace, odds and draw tabs, which leads me nicely on to...


New Draw Metric

We've introduced a new metric on the Draw Analyser and in the draw tab, called Percentage of Rivals Beaten, or PRB. I've explained more about it in this post, which I very much recommend you read if you haven't already.

The value of PRB over, say, win or place percent is that every runner in every race receives a performance value, with only the last placed horse getting 0. So, for example, in a six horse race, there would be a winner, one additional placed horse (as well as the winner), and four unplaced horses.

In the win percentages, that race would produce a breakdown of 100/0/0/0/0/0 (100% win for the winner, 0% win for the rest of the field).

Place percentages would have 100/100/0/0/0/0 (two placed horses, four unplaced '0' horses).

But the third horse has performed better than the fourth, fifth and sixth horses; and the winner has performed better than all of its rivals. PRB aims to more accurately place a value against finishing position. So the percentage of rivals the winner beats will always be 100%, and the PRB of the last placed horse will always be 0%, but in between there will be a sliding scale. In this six-horse race example, the second horse has beaten 80% of its rivals (four out of five rivals), and the fourth placed horse has beaten two home, which is 40% of rivals.

In a fair draw each stall, or group of stalls, would see a PRB score of 50%, or 0.5. And many stalls are within one or two percentage points of that. If a draw location has a PRB of 55%+ (0.55+) it is probably favoured; the converse is also true: if a stall has a PRB of 45% or less it may be somewhat unfavoured. Here's how it looks on the draw tab:

The table columns to the right hand side list PRB and PRB2. In this case we can see that high is favoured to a small degree and low commensurately unfavoured.

PRB2 is simply the PRB score multiplied by itself. What this does is accentuate the percentages: in practical terms it rewards those finishing closer to the winner than those finishing further down the field, recognising that horses may not be ridden out for the best possible placing if that placing is going to be eighth of 20, whereas they virtually always will if that placing is third of 20. There is more on how that works in the horse racing metrics post.

When looking at individual draws, I've introduced a metric called PRB3. Similar to IV3, it takes a rolling three-stall average PRB of the stall in question and its immediate neighbours. So, for example, the PRB3 of stall six would be the average PRB of stalls five, six and seven. It is, in exactly the same way as IV3, a means of smoothing the curve and making sense of draw data distribution. Here it is in action:


PRB has lots of potential applications in horseracing datasets, and we've started our adoption in the draw space. It will be especially useful when, as in the examples above, there is not a lot to go on in terms of runs, wins and places. There is still not a great deal in the PRB dataset but, by scoring every horse in each race in the sample, there is more data depth in which to fish.

That's all for this update. Very soon we'll be able to get stuck back into one of our favourite pastimes: messing around with racing data! And Geegeez Gold will have it well covered.


The Draw Analyser Challenge

Sadly, for those of us who love the UK and/or Irish racing, it looks like we're in limbo until at least June 1st. The good news, relatively at least, is that the odds of a restart on that date are shortening all the time. Assuming nothing untoward occurs during these next few weeks, we ought to be ready to get cracking just 20 days from now. Everything crossed, of course.

In the meantime, it's time to further tool ourselves up, and so I've come up with another challenge!

So that everyone can play I've made our absolutely awesome, best in breed, Draw Analyser tool available to all registered users; so if you have a geegeez account, free or paid, you can join in. This is for the duration of the challenge - one week - only.

Here's what I'd like you to do:

Step 1 - Visualisation

The first thing to do is to bring some logic to the party. It is all too easy to walk straight into the data without thinking about the problem at hand. That casual approach lends itself readily to back-fitting, because you're not trying to prove - or disprove - a theory. Rather, you're looking at the numbers and trying to work back from there. Whilst such an approach is not completely without merit, it is less rigorous than beginning with a notion of what you're hoping to find.

A way to do this when considering potential draw biases is to first look at the track layout. Let's use an example, York racecourse in this case.

1a. Go to our UK racecourses page and choose a course.

I've linked to it there, and you'll find it in the top menu under Courses/Fixtures.

Hint: try to avoid obvious ones like Chester; we're looking for angles that might not be over-exposed

In the top right corner of the racecourse page, you'll see a course map. Clicking on it will expand it and display the locations of the race starts.


1b. Scan for possible draw-affected race distances.

I'm immediately drawn to the mile (1m) and 1m1f distances because of that sharp bend at the top of the home straight that comes up fairly quickly. I wonder if, in bigger fields, that might inconvenience wide/high draws and, therefore, favour low to middle stalls.

So that's the assumption I'm going to test. (I think it's possible that in bigger-field two mile races there might be a similar bias for a similar reason given the number of left-handers the field takes, but we'll save that for another day).

Step 2 - Set up the tool

So now we need to set up the Draw Analyser. We're going to do this in a specific way so we test apples against apples, as it were.

The Draw Analyser has a series of options at the top of the page to allow us to configure things as we'd like.


So we're going to use a standard set of parameters, shown above and ignoring course and distance for now, as follows:

- Set 'Draw' to Actual - this will review the data based on the actual stall positions of the horses, removing any non-runners from consideration (so, for example, the horse drawn six would have an actual draw of five if one of the horses drawn inside him was declared a non-runner, and so on).

- Set 'Going' to Hard to Heavy (you could use Firm or, at most courses, Good to Firm, but we'll do this for now).

Your first 30 days for just £1

- Set 'Runners' to 10 to 16+

- Set 'Races' to Hcap (so we're only looking at handicaps)

- Set 'Dates' to 2009 to 2020

Once these are set up they will only change when we change them, as all data below the options area updates auto-magically 🙂

Now select your course and distance combination from the dropdowns.

Step 3 - Review the data

If we've performed steps 1 and 2 correctly we should have some data in the tool which may or may not support our theory. Let's review that to see if it is starting to tell us anything.

3a. Consider the course and distance draw 'all going' data

We can see from the chart that there's a lovely linearity - a straight line - from low to high. That is a very good start and normally things will be less cut and dried at this stage. N.B. Do make sure you check the left hand scale because you might see a line like this with very few percentage points from the top of the scale to the bottom.

The table above the chart tells us a number of things:

- There have been 65 races that match our criteria (wins column, 32 + 21 + 12) so a reasonable sample

- The win percentage drops as we move from low to middle to high; so, too, does the place percentage

- The A/E and IV figures for low are both above 1.00, a strong sign

3b. Consider going subsets

At some courses the favoured sector of the draw/track can change markedly on differing ground. For example, at Epsom and Brighton, jockeys will chart a course to the polar opposite side of the home straight on soft or heavy ground due to the way the camber leans and, therefore, the way the rainwater drains (it is always softest at the bottom of a hill or incline).

So we must check for any variance of going. I divide things into two simple subsets, fast and slow. Fast is 'Good or quicker', and slow is 'good to soft or slower'. [For all-weather, I include all AW going in a single range]

N.B. When using going ranges, the faster going must go in the top box or you will get no data returned.

Let's bisect our York mile data in this way:



In this case there is very little of note: the slow group has only a few races in it and it appears progressively tougher for high drawn horses to prevail, but there is not really enough evidence to be categorical about that.

What we can say is that the bias is 'going agnostic', that is, it manifests largely the same regardless of the state of the ground.

3c. Retest on date range subsets

Racecourse husbandry is an extremely complex business. I, and many others who value data in their wagering decisions, have given clerks of the course a hard time on occasion for their misleading reporting, but there is little doubt that all of them operate to a high level of skill in their field (pun intended!). Advances in irrigation (watering) and drainage, as well as tactical rail movements, have reduced or eliminated many historical biases and so it is important to check our data against different periods of time.

Dave Renham, our main resident draw expert (along with Jon Shenton, who takes a broader sweep in his course analyses), has recently taken to following the Mordin approach of rolling five-year subsets (e.g. 2009-2013, 2010-2014, 2011-2015, etc) and that is a great way to go if you have the time and inclination. For now, though, we'll break the data into two groups, 2009-2014 - the oldest six years in our database - and 2015-2019, the most recent five years. Again we're looking for any material change in the bias.

Hint: Remember to reinstate the full going range



While the sample sizes are quite small, the general principle is the same: low favoured, middle less favoured, high unfavoured. So we appear to have a bias that is consistent against both time and going. These are rare birds so do not fret if you don't find such a clean and consistent relationship with your chosen course and distance combination; after all, mine was cherry-picked for example purposes!

Step 4 - Fine Tuning and Scoring

The last step, assuming there is anything of note to this point, is to fine tune and score your course/distance combination. Actually, there is value in noting that there is little or no bias over a course and distance. No knowledge is bad knowledge and knowing that draw is not a factor in certain races enables an unencumbered focus on other aspects of the puzzle.

4a. Fine tuning

The fine tuning comes first; it's not really fine tuning as such, because we are working within the fixed parameters of field size, going and date ranges to resist accusations of convenience fitting.

But... it is sometimes the case that, for instance, very wet (heavy) ground or the biggest fields accentuate a bias, and it is worth noting that alongside the 'fixed parameter' work.

For my mile handicaps at York research, I wanted to see if a bigger field would emphasise the advantage to those drawn inside and the disadvantage to those drawn highest.

This is really interesting: in the 30 qualifying races, low has readily outstripped middle and high. But looking at the constituent draw data we can see that stalls six and thirteen, on either cusp of the middle draw section, have kept that group afloat. It does appear that either the inside stalls 'get away' or the wider drawn horses sweep around the outside to prevail. Those berthed in the middle have had a tough time being neither one nor the other of those things: not getting first run, and being potentially trapped behind horses in the straight preventing them getting the late run also.

That is conjecture on my part to some degree, but it's credible enough. Of course, I welcome alternative theories!

The IV3 chart at the bottom of the image above (IV3 being the average Impact Value of a stall and its immediate neighbours) demonstrates the middle drawn hinterland as well as the low-draw safe haven for punters.The constituent draw table reveals that ten of the 30 races in the sample were won by horses drawn 1, 2 or 3: that's a third of the winners from less than a fifth of the runners.

4b. Scoring

The last part of the process is to try to score the utility of any observed bias. It may be useful from an elimination perspective - that is, avoid high draws unless their form/value case is irresistible - or, more generally, from a 'mark up' perspective: in other words, bonus points to the case for a horse optimally housed.

The score should be more than a mere number, because there is normally a qualitative element to our observations as well the quantitative component.

For example, in my York mile example, I will score the bias as a solid 7 at this stage. When I've worked through a few more course/distance combinations, I might revisit that score and nudge it up or down a bit, but 7 feels about right for now.

The fact that it's somewhat 'feel-based' - we could use percentage scoring bases, but this challenge is not intended to be too academic in its rigour - adds ballast to the need for the quantitative element: some commentary on what we've discovered.

In this example, my final comments are thus:

York, 1m - 7/10 LOW

Strong linearity from low to high, the widest-drawn runners unfavoured. Bias has been consistent over time and on all going, and is accentuated in bigger fields (8/10 in 16+ runner handicaps), where the bottom three stalls have won a third of the 30 races in review.


5 The Challenge

This challenge may be considered a little more in-depth than the horse profiling one from last week, but it's actually about the same once you get into a rhythm. It would be easy to go through all of the distances at a given track in 30-40 minutes, and to select and review the most likely distance(s) in 15 minutes or so.

I'd very much welcome readers of a curious bent taking up the challenge and adding a comment below in the style of my York 1m note and score. I'll add it to the comments as an example, and hope it's not a lone comment!

Good luck,


Horse Racing Betting Angles: Part 3b, Bonus Module

In this bonus module, Part 3b, you'll learn about something I call 'mark up' angles. These are snippets of information which are not necessarily worthy of a bet in their own right, but will help me to form a view on a horse in the context of a race.

Again, if you've not seen the previous episodes, I urge you to start here.

In this bonus recording, we'll look at mark up angles for:

- Sires

- Wind surgery runners

And we'll also look at horse profiling within Query Tool. Adding a few of these to your Tracker for the upcoming flat season will be a VERY good use of an hour or two during this downtime!

Here's the video - I hope you like it.


p.s. If anybody has any questions, I will be happy to record a QT Q&A session to help you get you out of the blocks as quickly as possible.

Horse Racing Betting Angles: Part 3a, Query Tool Examples

This series of articles and videos has been designed to help inquisitive racing fans to understand more about the sport they love. Whether for betting or another, perhaps breeding research, purpose, there is much intelligence to be gained from looking beyond headline numbers; and Query Tool is a feature of Geegeez Gold which facilitates just such digging.

In the first part of this third part - part 3a - it is time to get into some examples. The angles highlighted have been selected in such a way that they provide a small amount of statistical 'nutrition' in and of themselves; but I hope their real value is in leading the viewer to conduct his or her own research along similar - or very different - lines.

I very much hope you enjoy it.


p.s. I strongly encourage you to take a look at the first two parts before diving into this one.

You can find Part 1 here

And you can find Part 2 here

p.p.s. the subtitles took a very long time to add, but that doesn't mean they're useful. Please do leave a comment and let me know if they enhanced your enjoyment or were irrelevant. I'll not be offended - far from it, if I don't have to spend another nearly six hours of my life doing that again, I'll be delighted!


Full video transcript

So before you start pressing or clicking any buttons in anger the first thing to think about is a scenario.

What we essentially want to do is test hypotheses or theories or ideas that we have.

Using the Query Tool

So what kind of scenarios can you see?

A few examples would be trainers in certain situations like maybe early season trainer form or trainers.

Maybe trainers by jockey, maybe big trainers

Not their number one.

What about the impacts of wind surgery? We can look at that, we can look at first time after a wind op.

Any number of times after wind op. We could look into the sires or jockeys or racecourses from a draw pace perspective. There really are any number of possible scenarios to dig into.

In the remainder of this video what I'd like to do is highlight some

examples of a given scenario. So for instance,

I will evidence one trainer and we'll find a jockey to go with that.

But you of course you go away and look at...

With trainers there are any number of UK and Irish trainers who have had

400-500 runners per year so they have big sample sizes to work with and you won't always find

valuable angles. Sometimes, very often, you'll come up dry but the whole point is if you if they were all profitable then everybody would be at it and the fact that we have to work a little bit harder not a lot as you'll see but a little bit harder represents a barrier to entry for a lot of people as well of course as not having

ccess to a tool like Query Tool


One other thing that I want to say before I start I've been asked a couple of times about parameters how should I set things up Matt? What sort of win strike rate should I look for? Where should I be with A/E and IV? What kind of return on investment should I be looking for?

The answer to this question is it's up to.

The key thing to think about win and to a lesser degree place strike rate they basically tell you how long you'll

go between drinks. A lower strike rate will mean you need a bigger bank and more discipline: if you can't handle losing runs you need a high strike rate to keep you

in the game as it were, and so there's no point researching an angle with a 10% hit rate because you could very easily go 35

qualifiers without a winner, and that's not going to work for you.If you normally bet quite short and you need lots of winners to keep you engaged then you're going to be looking you need to be.

The win percentage maybe 25 or 33%, you need to set it high

to suit your tastes.

Likewise if you want something that wins often you can use IV and say one and a half on IV and that's going to give you certainly relative to the peer group it'll give you

those qualifiers who win

one-and-a-half times or more than average. The point I'm trying to make, and it is a really important point,

worth taking time with upfront, is that

the angles that I show you,

and the angles that you research,

they might be exciting in terms of their profit or their ROI...

But if they don't fundamentally suit the way you bet,

you're going to give up on them.

This applies to any system or service you might be interested in trying as well: if the fundamental metrics of that

angle or system or service are not aligned with the way you see the betting world, with how you want to...

you appetite for risk,

the number of bets you want to place, another one is your tolerance for losing runs.

If the metrics don't match up against

those things which are personal to you

the angle is going to fail for you. Not necessarily because it's a bad angle or a bad system or service, but because it doesn't meet your personal requirements.

I hope that makes sense. It's a really, really important point and, actually, if you take nothing else away from this video, please take that away because that will stand you in good stead going forward. You need to find something that suits you. Not everything will.

Ok good right now let's crack on the first thing I want to look at then I'm recording this on the last day of March we are in a lockdown this year 2020 you might be in 3 years time content will remain valid in its conceptual form the data will obviously move on I hope I hope we have some racing in the next few years so for the 31st of March is traditionally,

in any normal year we would have just had

Doncaster and the Lincoln.

And we'd be started in the flat turf season.

I'm going to kind of pretend that the flat turf season has started and I want to look at early season trainer form.

So to do that I'm going to

MONTH and I'm going to choose March, April, May.

That's my early season.

I'm going to go to the RACE

box, just going to look at UK for now but obviously we could do this in Ireland as well.

RACE CODE, Flat Turf and Flat AW.

That kind of gives us a look at those trainers who in the month of March have been in good form on the all-weather which

gives us hope that they will take that early season form into the turf, but it also doesn't preclude those who don't bother with AW and go straight to the grass. So that's that, race code, so I'm going to change it two years as well.

I'll just click GENERATE REPORT and see where we're at.

And we've got 27,000 runners there.

Just a reminder of the filters so far we got lost two years March April May flat races in the UK.


Now look at this data by

Trainer. I'm going to now look at RUNNER

I'll click the

TRAINER radio button, now this is the order by button. I'm sure I referenced it in part 2 but just as a reminder: the left-hand radio grey disc, if you select one of those in this case, TRAINER

And then hit GENERATE REPORT which I'll do in a second.

Summary box instead of just having this overview row

will have a breakdown by whatever you chosen to order by: in this case trainer. But it could be jockey, gender, it could be headgear, whatever, so let's hit the Generate

Report button and see what happens. It might take a few seconds to come back.

Because it's quite a big dataset.

And there we are.

All sorts of guys and girls in this list sorted alphabetically by surname we've got these with, like,.

two runs and three runs and they're not really any use to us so I'm going to apply some filters in this.

Anyway, these boxes here. Hopefully my cursor

is making a nice yellow circle where I'm clicking.

I'm going to say.

At least 20 runs, although that feels like not enough probably.

I'm going to set my win percentage at 15 which is roughly 1-in 7 and again you know that might be to low for some people; I'll set my each way to 33%.

And I'm going to do 1.25.for

A/E and IV which will all be familiar now because you checked out the information from parts 1 and 2 in this three-parter.

Ok so I'm going to click update and as you remember this is a list alphabetically ordered and it's alternate row shaded. When I click update it's simply going to

hide those rows of data that don't match my parameters here. It's not going to look as pretty as it's not re-ordering, it's just hiding them so I'll click update.

And you can see that we've now got a much

smaller subset of data

for the last 2 years.

What I'm going to do is I'm going to

extend that out maybe to the

last five years

And obviously this is

150 percent

bigger data set than the previous one. We've got a few more entries in here, now what I like to do as a starting point is I sort

Actual over

Expected, high-to-low, like this.

I can see something else that I haven't done.

Oh I have, yes, Paul Nicholls has had a few runs on the flat.

Hmm, interesting.

I am interested in

Karen McLintock.

I'm not sure Garry Moss is training anymore, his sample size is much smaller as well.

Philip Hide not training any more.

I think we'll just go with those for the minute.

I'd better make these 1, I'm not sure I got enough data in the set.

Obviously what I'm doing here is I'm

mucking about with the parameters

to get a bigger, slightly more to look at in the first instance.

I'm kind of interested in

most of those. I'll just stick with these top...

He's definitely not training any more, I don't think he is.

These are quite small sample sizes.

I'm going to leave it at that just with those three there.

What I'm going to do if I just go back to TRAINER on RUNNER and if I open this box up,

by clicking not on the radio, not this side just clicking anywhere in here.

You will see that

those +'s that I selected

have... those trainers have appeared

within the trainer selection box. So if I now click generate report it's just going to bring back those three rows.

It's really important to remember to clear these because all of a sudden you will be wondering where the data is and it is there but it's hidden because it's not satisfying these parameters at the top.

I've done that now.

So I've got 3 trainers that I'm

potentially interested in early season.

Now I'm looking at Paul Henderson,

it's a smaller sample, just 22 runners.

And there's basically no profit there.

For all that the A/E is strong, it's just not going to give enough action I don't think.

So I'll remove him and you can see that the tick's gone there and Generate Report to get rid, so I've got two trainers of interest and just to remind us of our filters.

We got the last 5 years.

UK flat races March, April and May.

And you could actually just set that up

as as an angle as is.

And when Karen McLintock and Adrian Keatley have runners in the UK on the flat

in the early part of the season you would get notified on your...

within the race cards and on the report, that's actually something else I wanted to touch on so let's quickly do that. In the previous video I told you about

how to check your QT

Angles qualifiers.

And I told you about the report.

Which I now can't find, of course.

I didn't mention and I wanted to touch on here.

Is how they show up in the race card. As you remember there's no racing at the moment, so I can't show you how they show up in the race card but this is what happens.

You will see something like.

You would see a number that isn't 0 in the blue number column.

In this case it's a 1.

When you click on that, it will show you the angle in question.

and the Profit/Loss. Basically the data/metrics from that angle.

Now if you can't remember what the parameters were for the angle, if you just hover over it as I am now.

This will happen:

It will bring up your parameters.

Just over it and it will show you, in this case I did the last five years up to 24th July 2018.

5 Furlong flat handicaps.

With these five sires. So I quite like sprint sires.

Obviously the title 'Turf Sprint Sires' is very helpful. I could have put 'Turf Sprint Handicap Sires' or whatever, but this is a little angle that I have saved.

I wouldn't necessarily be backing this horse; it would just be another piece of data that I would throw into the mix when I was looking at this race.

So that's something that I wanted to bring out: the QT Angles

displays on the race card with the

blue numbers. Clicking on them shows the angle in question, hovering over the angle shows the parameters that you set up for that angle.

OK, good.

Right, let's go back to it.

So what I'm going to do I'm actually just going to save that as it is. Now, some people...

Good discipline really is to say right that's my...

That is my five year data...

But why don't we have a look at that, before we save it, let me have a look at it by year.

And make sure that, for instance,

all of the winners didn't come in one season.

You just quickly...

I've selected year here.

Clicked Generate Report and I'm going to sort it by year.

And we can see that...


Very few qualifiers.

In the full years 2016 through 2019 we can see that there was an approximately, well, there was a 20 plus percent win strike rate.

The each way strike rate was promising as well.

The win P/L has been a bit variable and last year was lower.

Quite a bit lower.

This year.

Two of them have placed so it's in the same bracket.

On a meaningless sample size of four.

It's too early this season obviously we lost the racing now.

I wouldn't be worrying about this year.

So I'm interested in this but I can see a

general degradation of the profit and the A/E figure reflects that as well.

I would be happy to save this Angle and as I say use it advisedly rather than backing these horses blind: it would just be an aide memoire to me that McLintock and Keatley

are trainers to keep on side in the early part of the season.

Your first 30 days for just £1

So then I'd add that to

my QT Angles.

"Early Season Trainers", Add Angle,

And then that's done.

And, of course, like everything else they're all zeros, but that is one angle and you could have an early National Hunt season trainers one, a summer jumps trainers one.

You could have a

sa Summer jumps by track angle. So there are lots of different... this is one example, but there are lots of different other ways that you could cut this data.

So that's the first one. Right let's look at trainers and jockeys now so I'm going to hit my reset.

I'm actually going to refresh the page entirely.

Now this time I'm

going to look at

two years of data

I'm going to go to.

Ireland, just for fun, just to change things up a bit.

I'm going to sort by trainer.

Just do that because I want to see who's got the most


There probably is some merit in looking at trainers who maybe only have 30 or 50 runners a year.

But really I think the value is looking at the big

Big datasets.

And looking at things that

are maybe less obvious

to the man or woman

in the street.

I'm just going to change this to FLAT (TURF/AW) again

And now we've got a small subset, well, we've got a large number of trainers but a small subset of

essentially volume trainers.

The trainers I'm going to be interested in

I want 100+ wins

And that's going to quickly sort things out.

And then I'm going to sort

High to low.

And let's have a look at Aiden O'Brien. Let's select Aiden.

Generate Report, and that's going to bring just him up. I've got to remember to clear

my filters data here.

Now, I'm gping to say, show me Aiden O'Brien's runners in the last 2 years on the flat.

Sorry Aidan O'Brien Irish runners in the last 2 years on the flat

by jockey.

Click the JOCKEY radio button, click generate reports and then in my summary box.

I got all the different jockeys that Aiden has used in the last two years. Now again we've got these ones and bits and pieces, they're not really meaningful so let's sort by

wins and we'll say, "right well we're just get rid of

anybody with

less than

20 runs", let's say.

Small subset here, again sort by A/E.

And we've got.

Messrs Hussey, Moore Donnacha O'Brien,

Emmet McNamara, Seamie Heffernan,

Paidraig Beggy,

and Wayne Lordan.

Wayne Lordan

is an immediate chuck out and if you're a layer that might be interesting: an A/E of 0.53.

on 150ish.

runners is terrible.

In fairness to him, he's almost always on a second, third or fourth string but nevertheless...

And again you'd need to check

Betfair SP because he might be riding some massive priced horses, but on the face of it these are eminently avoidable.

19 out of 20 get beaten.

5 out of 6 are not even in the frame.

These are not horses to go to war with generally.

At the other end Ryan Moore is quite interesting: 34% strike rate and a small profit, in fact a reasonable profit

at SP. So we'll have a look at Ryan.

Let's take Ryan Moore and Hussey and O'Brien is now training so he's stopped; we'll have McNamara and Seamie Heffernan as well.

The reason I've done that is I've got them here now so what I can do is I can look at them individually and I still got these names here to come back to. I'm going to have a look at

Ryan Moore first.

I want to look at

a bigger data period.

So I'm going to go back 5 years.

And I'm going to sort by year.

And order this by group.

You can see here...

that essentially

what happened

in the last 2 years.

Is not replicated in any of the previous three.

This is kind of precarious territory now because we're not seeing

a replication of the Actual

over Expected, we're not seeing a replication of the profit and loss.

We are seeing that in the last couple of years Ryan's IV has risen.

Now, our job as researchers

is, if you remember the point from part 1, of logic logic logic...

If we can come up with a reason

for this, if we can explain why

in 2017

It was not good, and in 2018 it was good,.

then we've got a bit of a chance.

And there is one credible reason, and it is this.

If I go back to RUNNER

and JOCKEY. And I'm just going to look for

this guy, Joseph O'Brien.

So if I do that and then sort by


Right now what I want to do is I'm ging to go to my dates and sort that by year.

And what we can see is that

Joseph stopped riding in 2015.

So that would partially explain

these data here. So 2015

Joseph had

plenty of the good Aiden horses.

It doesn't explain 2016 and 2017.

Notwithstanding that the A/E figures for those years are kind of more acceptable than

this one here.

When Ryan was competing in Ireland with

Joseph for the Aiden

rides (apologies for

first name terms).

So where do I get to with this? And again these are the kind of situations that you'll find yourself in when you're doing this.

You've got some kind of make value judgements.

Actually I should have cleared that I don't think it's going to make and difference.

I should have cleared that before.

So we've got a situation here where recent history is promising.

Longer-term history less so.

We've got kind of a partial explanation.

We've got a full explanation for the year 2015.

You can see that as Joseph stopped riding - in 2015 Ryan Moore only rode 27 of Aiden's horses in Ireland.

And in subsequent years he's ridden more, as you can see; and that is probably a factor in these numbers I think on balance it's definitely something worth

keeping in mind because it's the kind of thing...

It's one of these 'Hidden in Plain Sight' angles, it's the sort of thing that everybody thinks must be overexposed.

And it's potentially not.

Now what you might do this in the last 2 years there's kind of 200 runners there you might look at whether it's 2 year olds or Group races only you might look at

which particular

race types

O'Brien and Ryan Moore have combined with for the most success.

And that might be your angle.

This is a trainer / jockey combination and, you know, who would have thunk that

O'Brien, the best trainer in the world or certainly in Britain and Ireland, and Ryan Moore, the best jockey in Britain and Ireland, I think both of them have only got one peer and they're a partnership as well.

Gosden nd Dettori

Who would have thought that those highest of high-profile trainers and jockeys would be

borderline profitable to follow blind.

It really is quite remarkable and it's and it's worth knowing.

Saving it to your angles if that's something that you want.


Let's do a slightly less obvious one.

This time I'm going to look at

UK trainers on the flat.

The last 2 years here, you see that there.

And from my RACE conditions I'm going to say UK.

Race code.FLAT (TURF/AW)

And then I'm going to look by trainer.

This is quite big dataset, so it will take a minute for the data to filter in. The query is complete and then it takes a second for your browser to order the data my browser is being told what to do.

And it's got to create this very big table.

And that takes a minute or a few seconds to do.

Right again we've got very small numbers in here so I'm going to sort by number of winners.

So I can see where a sensible cut-off point is.

And 150 wins

gives us plenty

to go at.

Sort by win strike right, now we can see that we've got David Evans who has

volume but low strike rate. I don't really want these

super low strike rate trainers so I'm going to put 10% in.

which actually doesn't get rid of many.

I just leave it like that I think.

So we've got quite a bit of data to go at.

Some trainers,

like Mark Johnson uses Joe Fanning and Franny Norton

extensively and there actually aren't that many left around that. Other trainers like John Gosden will.

use Frankie and Rab Havlin for the vast majority of his. Let's have a look at Johnny G actually.

And Karl Burke

And maybe Roger Varian

So what we've got here are

three trainers who all perform better than average, one of them is a standout and that is Gosden.

We're going to look at Gosden first and again if you remember we can just deselect the other trainers.

That's Johnny G's - again forgive familiarity - that's his overall 2-year

record on the flat. I want to look by jockey.

Select the JOCKEY radio button and generate report and here are the data.

Robert Havlin has had the most rides and winners in the last two years Frankie is quite selective.

Let's sort by A/E.

And again we want to get rid of the small sample sizes.

Let's say at least 15 wins,

Now we've got a much smaller

more meaningful dataset. The first thing to look at is Frankie (Dettori).

See he wins 30% of the time


So let's have a look at that actually overl the last 5 years, I think it might be a profit over the last five.

Break-even, but at exchange prices that will be a profit. We'll go back to two years.

So we got Oisin Murphy, Jim Crowley, Frankie Dettori, Rab Havlin, Nicky Mackay and Kieran O'Neill.

The strike rate for Nicky and Kieran is 20% or lower which in the context of the group

is not really at the level I would like to be, so we'll look at just these four guys.

So we've got four here now.

What we can do is

Rob Havlin.

It's going to be hard, I mean there might be some situations where he's

profitable to follow.

Potentially when he's on a second string so when

he's riding

a horse at

a bigger price to Frankie.

That might be something worth looking at, you can do that with odds by selecting him but I'm going to

deselect him for now.

Generate report and I've got three in here.

I want to look at these guys over the longer term, we could just quickly look at Frankie but I want to look at.

Oisin and Jim as well.

And we can see that

Oisin Murphy

When he rides for John Gosden

I mean 40%.is ridiculous...

It is a small sample size.

And these 30% numbers

certainly Frankie's, on

a bigger sample size are remarkable.

If you're betting in a race where Gosden

has got one of these jockeys up and you're not betting it

You've only got 70% of the winners to go at. Now that might be absolutely fine.

It's kind of a meaningless or misleading start in and of itself but you need to know that these guys are winning a lot of the time. Whether they're profitable or not is another question: in the case of Oisin Murphy who is

the retained jockey for Qatar Racing and it may very well be the case that

a lot of those 50 horses that he's ridden for Gosden in the last five years were for his retained owner.

That's by the by, what we need to know is that this is a guy worth following. So you might save this angle as...

Gosden and Oisin.

And add it to your setup and then when they have a qualifier you get your Gosden and Oisin...

You get your blue number here and it will tell you the numbers and you'll be able to factor that into your overall consideration of that race. It might be you might want to bet those blind or you might want to bet them more selectively as I do. But either way you have that data right in the card there and also on the QT Angles Report.

So those are jockeys and trainers. Maybe we'll just look at one more. Let's go back to

RUNNER and we'll look at the trainers.Let's have a look at Karl Burke

So I've selected TRAINER Karl Burke and I've still got this by JOCKEY.

I want to look at Burke's

rider selections in the last 2 years.


Again I'm going to sort it. I want to get rid of the small numbers so let's

cut that off at 50, that's fine.

Sort by A/E.

Ben Curtis is the guy that kind of immediately

jumps off the page.

Let's have a look at Ben.

Now what I want to do is I want to look I want to look by year.

How's things.

Let's go 5 years and extend it out a bit.

That year actually if we look at

the win strike rate in recent years,

2017 and onwards, you can see that the strike rate is around


But last year was down.

This is one, again it's another value judgement, you've got to kind of say,

"Right, obviously if I got a year like

2017 or 2018 I'd be thrilled to be following these but if I got a year like 2019 where the strike rate was down

and I might be in the hole a fair bit at some.point,

would I be able to stomach that?"

The answer for most people is NO

Only you know the answer for you.

I'd be absolutely fine with this because, again, I'm not backing them religiously anyway. I'm missing winners but I'm missing plenty of losers as well by being selective.

What I want to do with Karl and Ben.

is I want to

look by MONTH...

I want to see, because most trainers have seasonal ups and downs, and looking at trainers by month is a valid thing to do, and often it is

quite instructive.

So I've selected order by MONTH and Generate Report. .

Now we've got some interesting


Remember our filters, specifically Karl Burke when Ben Curtis is riding

On the flat in Britain in the last 5 years.

See that there are some ups and downs here and the easiest way to

visualise this is with the CHART.

This is something else I wanted to show you: when you've got a...

When you've got a number of

variables in your parameter, so I've got 'by month' here and I've obviously got 12 months - 12 variables in my parameter.

Or 12 parameters in my variable, I'm not even sure which of those is right! Anyway,

what our charting software does is it takes half the dataset, or sometimes a smaller percentage. But if you click .

in the top chart,

it will show you everything. Now sometimes, if you've got like a 1000 trainers in here that's going to be not going to be able to make sense of this so what you can also do is if you click and drag

you can select

a section.

of the chart to look at in more detail. And when you've got 1000 in here that selection I've made there which is, what?, about a quarter, that's still going to be 250-odd so I might actually be only wanting to

look at a smaller subset like that.

A single click and you'll get the full dataset. Right, so here we've got Burke and Curtis.

It's sorted by Win PL I'm going to sort it by A/E, which is a good friend of mine and again clicking in the chart [to view all data].

What we need to note here.

1.0 is the line of interest in A/E (and to a lesser degree IV).

And what we can see here.

In the early part of the year.

Certainly January-February March.

And the late part of the year - October November December - this is a period that obviously aligns with the all-weather.

Karl Burke and Ben Curtis have had a good time of it.

In the summer months,

less so and particularly less so between

July, August

and September

I mean that's perfectly legitimate in my opinion.

To accept that seasonality I mean if you look at strike rate.

The average for the year, you can see this at the bottom, it's 16% overall.

And in July it's 10% or 9% in August it's 5%.

And in September it's

12%. It's much lower

than the overall averages in

April May are much lower as well so I wouldn't be including June and excluding April and May.

I'd be either including April and May as well as June, or excluding April through June, if you see what I mean. You've got to put logic behind the theory: now in this case the logic is probably these guys are

mustard on the all-weather and we can very easily check that. If we just

select the ON button here it's going to put all the months on I'm going to take out

May to September.

Is a little bit convenient maybe.

I'm going to do that, and then life looks more rosy obviously but what I want to do now.

Is I want to look at


There actually isn't a huge amount of difference.

So the theory about

most of their winners being on the all-weather is debunked.

They look absolutely fine on the flat turf as well so that's interesting that's good. One other thing that I might look at is by handicap or non-handicap.

And again.

Much better in handicap so might though it is profitable in

win profit and loss

terms in non-handicaps but if you look at the A/E that would give you cause for a slight reservation. Certainly

all of the metrics are better in handicaps.

I might change that to handicap and I might revisit my dates and see if that makes

any difference in the summer months.

And actually what it does

is it kind of reinforces

the previous date range

that we selected, which

was October through to April.

So if we delselect the summer months

We've now got...

We've essentially combined the two scenarios we've looked at so far which are kind of a sub-season.

It's sub-season trainer form with trainer by jockey.

Generate the report and we've got a nice little angle here which has been extremely profitable. It's worth looking at by year.

And we can see again that there was a

losing year in 2016.

So, again, are you comfortable with that? The answer might be no.

Generally speaking this is an approach that in the last few years has been a really

good one to have onside, so I'd always be mindful of Burke and Curtis

teaming up in handicaps in in the trainer's good times, which are October through to April.

That's an angle that I think it's worth saving.

So that's saved to my Angles now..

I want to show you one more. I am conscious of the length of this video and I might break it up into two recordings.

I will do that so I'll do this last one on trainers.

Actually I have got one more on trainers, so I'll do that in a part

3b if you like, and some people will obviously have got the general idea by now and choose not to look at

the angles highlighted in Part 3b, others will want to look at those as well.

I mean I would encourage you to look because I think,

not so much for the specific angle, but there are some more scenarios I'm going to highlight which might give you ideas to go and research on your own.

And I think there's plenty of value in that.

Let's go we're going to do another trainer jockey combo.

I do loves me a trainer jockey combo as long term

subscribers will know.

This time we're going to look at Red Raif, as I

somewhat unflatteringly call him.

Mr Beckett, who is an excellent trainer.

And a passionate man.

Somewhat political and not fully aligned with my own view of

the world. But that doesn't make him right or wrong, it just makes us different.

Anyway it is his ability to condition horses that we're interested in here so let's retain focus on that.

Beckett as you can see has a 16% strike rate in the

last two years. If we extend that out to five years, we can see he retains a very consistent strike rate.

And if we look by year,

we can see that he's...

...ignore this part year which is unrepresentative, as you can see by the number of runs, but in the main he

is consistently around 14% to

20%, average 16.5%, very solid overall figures from which to work. So what I want to do is I want to look at...

As you can see down the bottom here we've got two and a half thousand runs

So we've got a bit of data to work with..

So let's see if there are some sensible subsets within that.

We might look at

RACE CODE for flat turf and flat all-weather.

We can see that his strike rate again is consistent.

Nothing really

of interest there.


Is he better with sprinters or middle distance horses? He doesn't have a huge amount of runners

at sprint trips.

The ones he does are largely

consistent in strike rate terms, so

nothing really going on there.

Handicap or non-handicap?

Hmm, now that's interesting.

The strike rate is not

massively different, but it is notably different, kind of 10%.

16 + 10% of 1.6 - 17.6 and it is 17.43, let's call it 9% better in handicaps.

And we've got a bit of a chance looking at the A/E figures here and Win PL on a big sample size so I'm going to look at

'Red Raif' in handicaps.

And then we've got this summary number. Now let's look by


That's interesting.


Longer-distance races look

potentially more interesting.

But what I really want to look at is by jockey.

So let's open up the JOCKEY radio button.

Generate report

And get rid of some of these meaningless .

samples, so let's say we want.

we'll start with 20+ and work up from there.

Sort by Actual / Expected

And we've actually got some really interesting players here.

Now Fran Berry has retired and he and Pat Dobbs used to ride a lot for Ralph Beckett, as did

Richard Kingscote as you can see. They had the least good data in terms

of A/E and indeed

in terms of Impact Value which is a reference to strike rate as well so they are easily excluded.

Higher up the list we've got

the likes of Sylvestre De Sousa, Josephine Gordon

I think if we put a

win strike rate of at least 15%

Get rid of some of these so we can focus more clearly and an each-way strikerate of 33%.

Now we're getting to the juice of it. And a problem with Sylvestre is that he's a fantastic jockey - that's not a problem - the problem is that everybody knows he's a fantastic jockey.

Even in this loaded situation, Beckett in handicaps, where

he places his horses very well clearly.

The strike rate is high but we're never going to be able to get rich with this guy.

I think I'm going to look at the other four

You could do more with this but really, it might be worth looking at gender - Beckett is extremely good with training fillies and mares. He's won the Oaks a number of times.

There's not really much difference.

Male horses tend to win more often the female horses.

That's just a function of

genetics I suppose; age is worth having a look.

I just want to sort this by group, so I can get a feel for the linearity of it, if you like.

Rather than cherry-picking

based on A/E

or profit.

Most of his runners are in the 2 to 4 year old age group, it might be worth focusing only on the the younger horses: 2 and 3 year olds.

I think that's probably a legitimate thing to do.

In this example I'm going to leave them all in but you might choose to focus only on those that small group you can see that they're the sort of 5, 6 and 7 year olds have very few runners. They've had 34 runs between them whereas 2-year olds alone in handicaps have had 45 runners in the period so I'm just going to leave it as is and

I think we've got a nice little trainer jockey angle here so Ralph Beckett in flat handicaps.

When he uses Oisin Murphy, Rob Hornby, Louis Steward or Harry Bentley. Now this is a five year view and again it's definitely worth looking at the year by year breakdown.

We can see that there's a

gorgeous consistency here that is an angle researcher's dream such is its

annual profit and its strike rate of

20+% (again, ignore this year because.that's

a small number of runs in the year so far). I mean that's really quite interesting.

We might look by month as well just to see if he has any seasonality to his form.

The easiest way to do this in a chart.

The 1.0 line is here and we see

again in June and July

High summer when trainers are running horses left, right and centre,

firing a lot of bullets,

it's quite difficult to retain

the higher strike rate.

And that has an impact on profitability and therefore A/E.

You might choose to leave

June and July out; I'm not seeing enough there to justify it for me so I'm going

to leave them all in.

Notwithstanding that June and July are

slightly less appealing.

I think it's a really solid angle and I'm going to save it to my QT Angles.


Alright and that's another angle.

And that is enough for this video I think. I hope

you've seen some interesting angles there. More importantly, I hope you see

some of the considerations that we need to work within when we're considering what might be an approach that suits us and when we're considering

the legitimacy of

data in terms of

it's long-term or future profitability potential.

And I hope this may have inspired you or encouraged you to maybe have a crack at researching some angles yourself. If it has and you've watched this video from the blog...

Please do leave a comment with anything that you'd be happy to share. You might want to keep some of them for yourself, and that's fine, but if you're happy to share that would be fantastic as well. Even if it's

a generic approach.

So, again, like a scenario that people could go away and look at their own


OK, enough already, this is Matt Bisogno saying thank you very much for watching this part 3a

of the Query Tool series. I hope you got some value from it, I'll be back the part 3b very soon.

But, for this one, byee for now.

Horse Racing Betting Angles: Part 2, Query Tool Intro

In Part 1 of this three-part series looking at horse racing betting angles, I talked about research principles: about knowing what works for you, about the importance of logic and a lot more besides. It's a foundation piece for the next two parts and, if you've not read it yet, I'd strongly encourage you to do that first. Here's the link: Horse Racing Betting Angles Part 1

Parts two and three are video-based for now, though I will endeavour to get transcripts at some point. The middle piece, then, is below, and it provides an introduction to Query Tool, Geegeez Gold's main research module. It can be used to drill down on courses, horses, trainers, jockeys, sires, damsires, and plenty of other things besides.

In this video, you'll discover what Query Tool (QT) is, where it lives, and how it works. You'll see how to visualise your analysis, display qualifiers and, best of all, save your research so that it is recalled when relevant, i.e. when there are qualifiers in the day's racing. Click the play button to watch Part 2.

In Part 3, which you can look at here, we'll look at some examples of angle research, produced with Query Tool. Each example is one element of a group of entities which can be researched. As such, there is ample opportunity for curious readers/listeners to try things out for themselves. Look out for that in the next couple of days.


Horse Racing Betting Angles: Part 1, Research Principles

To win at betting on horses, or indeed anything, one needs either to be lucky or to be smart. Ideally, one needs to be both. The best tactic of all is to use smarts to make your own luck, and that is how we'll proceed in this three part series. In this first episode we'll consider the cardinal principles, without which anything that follows will be precarious as a basis for betting decisions.

What is a betting angle?

Let's start at the start, and define what exactly is meant by a betting angle. For me it's a deliberately vague term because I don't want to be reduced to mechanistic wagers spat out by my computer's 'brain', even if whatever comes out is a direct result of what I fed in. I'd rather be advised or reminded of a nugget of information when I'm previewing a particular race.

Put another way, if my research tells me Trainer X has a great record with Jockey Y that will generally not be enough in itself for me to place a bet. But it will encourage me to look more closely at the overall profile of the runner around which Trainer X and Jockey Y are combining.

In other words, I want as many extra pieces of information - snippets which will generally be unknown to the vast majority of punters - as possible when I'm weighing up a race. What I don't want to do is simply back a list of horses generated from my angles.

That is system betting, and it works for a lot of people. If that's you, you will find plenty of utility in this series, but my main focus is on micro-angles which will add a point or two to the case for a given runner without necessarily commending it as a bet.

Betting angles then are snippets of information which can help decipher a race and potentially identify a dollop of otherwise unseen value.

No system or angle is God

Horse races are loose forms of organised chaos. An average of ten large animals, steered by small animals, with each other and/or obstacles in their way: there is plenty of scope for things to go wrong. Unsurprisingly, things frequently do go wrong. Thus the best horse often does not win. Rather, the best suited horse to conditions, or the best placed horse from the break, or the horse that makes the fewest mistakes, usually wins.

These kind of 'chaos variables' are generally not factored in to the price of horses at the top of the market, meaning such horses can not normally be considered value bets. Their chances are well advertised by the good judges in the racing media and the weight of money from lazy punters ensures their followers will eventually suffer death by a thousand poor value betting slip paper cuts. Or something like that.

My point is that we need to build in enough latitude to account for what used to be known in my software development project management days as OSINTOT's ("Oh Sh!t I Never Thought Of That"). Stuff happens, regularly in horse races, and our wagering approach must be sufficiently resilient to handle it.

No system is perfect, no angle immune to the bettors' scourge, variance: again, as I like to say, "after a good run expect a bad run; after a bad run expect a good run". Such is the nature of the beast.

For ultra-contrarians, the best time to get involved with a proven tipster or a solid-looking betting system is in the howling teeth of a downturn; after a bad run expect a good run. But only if you firmly believe in the underlying merit of the approach behind it.

Designer babies

We all want to be beautiful/handsome. And we all want to back big-priced winners on a regular basis. But, sadly, we have to play the hand we're dealt. You might have smouldering Dean Martin looks, but I get reminded more often than I'd like about my better than passing resemblance to Mister Bean. Such is life.

And so it is with betting systems. We hanker after the golden goose, the method that gets all the girls. But that's not what we need. What we need is a steady little portfolio of pointers that keep us honest, content and on the right side of both the bottom line and sanity. That is achievable, sustainable, and far more nourishing than a golden goose. How B-O-R-I-N-G would life be then?

This game is about little fish tasting sweet. It is about the thrill of the chase, about engagement and fun: solving the puzzle lower down the lists where others have fallen into its top of the market traps.

There is no such thing as a golden goose system, thank the deities. But there are myriad in's that offer slivers of value, shards of profitable light, to those who care to seek them out.

This series is for you.

A bit about you

On that point, then, let's talk about you.

One of the best pieces of business advice I ever received was to create customer avatars. A customer avatar is a very specific definition of the core client of a business.

Understanding this has helped geegeez.co.uk to stop focusing on 'all horse racing bettors' and home in on 'horse racing bettors who know they want more information than is available for free elsewhere, and don't mind getting their hands dirty in the quest to find their own value picks'.

That's less catchy, and is a very (VERY!) small subset of 'all horse racing bettors', but I can talk to almost every single one of these guys - you guys - as an equal, and expect that what I say will largely resonate with your own general outlook on the racing and betting game.

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Back to you and, specifically, your betting approach. If you've read this far, you almost certainly are interested in finding your own betting angles - the good Lord Sugar knows this introduction has been long enough to disqualify those who are not!

But a betting angle that works for you will not necessarily be the same as one that works for me, or that works for the next reader. Some examples will help.

Betting Angle A has a 3% ROI on more than 10,000 selections. That's 300 points profit. Nice right? Well, maybe.

What if Angle A identifies 40 bets per day? What if the average odds of winners are 25/1?

The downswings with an approach like that could run to many hundreds of points. To operate it profitably would require a very large bank, very small unit stakes (in percentage terms), and titanium sphericals. The profit is attractive to all; the modus operandi suitable for very few.

Let's try another.

Betting Angle B has a 9% ROI. It finds roughly 40 bets a year and has been profitable in four of the last five years. In the other year, it lost 28 points. Could you handle that loss and still retain belief in the angle? You probably could if you were being selective when playing it, and if the 40 bets were in a particular context - for example, early season trainer form.

Whether you could or you couldn't, the key here is that while we may all be similar in terms of our general aspirations from the game, we are all different in how we can scratch that itch.

We have different bankrolls, different appetites to risk, different styles of betting, different amounts of time to invest in finding our bets, and so on.

That diversity is to be celebrated: it ultimately means we'll land on different horses and back winners on different days. It won't stop any of us from being profitable or from enjoying our betting as long as we recognise our own terms of reference before getting stuck in.

It is very well worth taking a few minutes to think about your approach, and how optimal that approach is for you. If you use our Bet Tracker tool, you'll have a better insight than most into the way you bet, what works and what needs more thought.

What to look for in a good system/angle

The first thing to say here is to refer back to the previous section: make sure any angle you identify looks sustainable in terms of the way you play. If you need a winner every third qualifier there is little point in deploying an angle with a 10% strike rate; you'll give up on it after a few losers which, almost inevitably, means before you've made any profit.

If you only want to place one of two bets a day, there is little point in identifying a great angle with an average of six bets a day. You'll immediately feel uncomfortable with the different staking and wagering regimen, and that is not a position of strength from which to enjoy the sport.

Any research you undertake needs to be mindful of how you bet: how often, how risky, and so on.

A good system, then, will speak to you personally in terms of its numbers. It will fit your appetite for risk, volume and available time. If it doesn't, it's only a matter of time before you pull the plug, profitable edge or not.

Aside from the personal elements, there are generic precursors to good angles, too.


The first, and most crucial, component of angle research is logic. An angle should be explainable in a shortish sentence and, if you were explaining it to a fellow punter, she should not spit out her beer in disgust at the case you make.

It is never enough to reason, "well it's profitable". If you can't explain why it is profitable the approach is very likely built on foundations of sand.

It might be fine to have an angle based around big trainers' performance in Saturday handicaps. But it would never make sense to create an angle around performance on Mondays, Tuesdays and Thursdays, for instance. There's simply no underlying logic.

Likewise, trainer angles where there are gaps in the months which qualify make no sense; conversely, however, plenty of trainers have certain parts of the year/season when they're in bloom. As long as there is a consecutive nature to the period, that may well be predicated on the schedule of the yard's year.

Just think 'why' for every variable within your angles. If you can't explain it, you should probably bin it.

Less is (usually) more

The always compelling Tony Keenan wrote about focus for optimal betting decisions in this excellent article. In it, he refers to neuroscientist Daniel Levitin's contention that we should unburden the brain by placing information in the physical world. Keenan talks about 'to do' lists as an example but it is equally true of betting angles: we should move these from our cluttered crania to, well, to a query tool or other aide memoire.

He goes on to reference Levitin's work on something called optimal complexity theory. Here's Tony:

...the idea that too little information is no good but so is too much. This applies with any decision we make, like buying a house or car say. Having too many parameters to consider leads to confusion in decision-making, with humans apparently unable to process more than ten variables for any choice, the optimal number being closer to five.

Betting angles should be simple in the main, predicated on sound logic, and often 'hiding in plain sight'. The more convoluted they are, the more likely the creator has added an extra variable or two to filter out some inconvenient truth. This is a subjective area and one where common sense is our greatest ally. Less is usually more.

Be wary of small sample sizes

The nature of looking at horse racing statistically, which is essentially what angle research boils down to, is that we are invited to make inferences on insignificant sample sizes. The conundrum is thus: too large a sample and the angle is well known and profit gone, too small a sample and the angle is unreliable and may be a fluke.

So what to do? Two things...

1 Seek a happy medium

Somewhere in between those two unsatisfactory sample size groups is a reasonable amount of data and the chance of profit continuing in the short- to medium-term. Where possible, look for as big a sample as you can. An angle with eight winners from ten runners looks fantastic, but how sustainable is that? It's impossible to know on such limited evidence.

One thing we can do in such situations is to widen out the search. For example, if Sire Z's progeny have had eight all-weather sprint winners from ten runners, how does that compare with his turf sprint winners? Or with his all-weather runners overall? We're looking for greater assurance in larger numbers. Chances are we'll still be dealing with relatively small samples, but we'll have a better feel for the sustainability of the micro-micro-sample of ten runs.

2 Proceed with caution

Wise men say only fools rush in
But I can't help falling in love with you

So sung the immortal Elvis Presley, and he wasn't wrong. Once you've satisfied yourself that there at least might be merit in an angle, go forward carefully. Do not rush in. Only fools rush in.

Such angles are prime contenders to be considered in the context of the race overall rather than bet blind. For instance, a trainer with an excellent record with handicap debutants from a tiny sample: is there anything else about this runner to corroborate its chance? Has it been off for more than a month? Is it stepping up in trip, or down in class? Is there a notable jockey change? Has there been money for the horse?

It doesn't take long in most cases to see whether the qualifier should be a 'proper' bet, an 'action' bet, or a watch and squirm job. (For me, there is no such thing as the last named. I'm either betting to win a few quid, or I'm betting to win a cup of tea and a sticky bun, or I'm not betting and I won't cry if the horse wins).

Profit is not the best measure

Most angle researchers have an unhealthy obsession with the Profit/Loss column. Of course we are trying to secure a positive return, but there are any number of traps for the greedy punter whose alpha and omega is pee and ell.

Harking back to what suits a particular bettor, and mindful of the small sample sizes that often manifest, it may be prudent to focus on each way percentage, percentage of rivals beaten (PRB) or percentage of rivals beaten squared (PRB^2). The last named pair, especially PRB^2, are very interesting metrics that will make their way into Geegeez Gold later in 2020 and I will cover them in greater depth at that time. For now, though, Gold users might look to each way percentage as a way of - somewhat artificially but perfectly legitimately - extending the sample size in question.

In terms of profitability, A/E (Actual vs Expected, more information here) is a solid barometer of ongoing value. It's a simple enough concept, where an A/E of greater than 1.00 is considered a positive, an A/E of less than 1.00 is considered a negative, and the further away from 1.00 the number, the better or worse is the expected merit. The A/E column can be found within Geegeez Gold's Query Tool, a tool that will form the cornerstone of parts two and three in this series.

Review, and Realise

Once you've found your angle(s), stored them, and started to bet them, there are two important 'maintenance' jobs to take on. The first is one of review. No matter how large or small the research sample was, every qualifier thereafter swells the knowledge base. Returning to your set of angles on a regular - maybe quarterly, but it depends how much action an angle throws up - basis is excellent discipline. Don't get too hung up on profit and loss from quarter to quarter, but rather focus on whether the horses looked likely beforehand, took a degree of support, and ran well even if in defeat.

Through this review process we start to realise - make real - the angle. A trainer becomes someone whose methods we get to know; likewise a sire, or a course profile, or whatever. We must make friends with these entities, ask questions of them, become more familiar than the market. This is a lot easier than it might sound, particularly in terms of the early markets, which are heavily focused on 'top down' information such as basic recent form, newspaper tipsters and fashionable trainers and jockeys.

'Bottom up' intel - first start in a handicap, favourable draw/pace, no name trainer with his job jockey, and the like - is factored into the market later. This late intelligence is generally underpinned by people close to yards who want to bet, and they can't get a meaningful bet on until nearer the off time. As angle punters we have to second guess them: we'll generally not nick their price, but can nab a few quid at 'ignorant odds' before the smart money arrives.

More often than this, though, are the occasions when we realise that the first flush of love was misguided; that we rushed in as fools, or maybe merely flirted dangerously with a dataset which failed to substantiate itself for the application of further evidence. Reviewing and rejecting these false dawns (no offence, Dawn, if you're reading!) is as valuable - arguably more valuable - than finding a great angle: the first job is to try not to lose money, the second job is to try to win money.

Nothing Lasts Forever

The final point to make in this overture to Angle Research is that nothing lasts forever. You will know you have found a great angle if the strike rate remains largely the same over time while the profit diminishes to a loss. That is simply a function of market awareness and is the lot of any and all statistical edges.

The game, of course, is to continually reinvent our portfolio.

Every week, month or year, there are new trainers waxing and old trainers waning. Likewise sires and, to a lesser extent, jockeys. Tracks change their drainage and, in so doing, reverse their draw biases. Surfaces get relaid and the front-running bias is mitigated as the kickback to later runners becomes less severe.

It's the circle of life, and all the joy within: there is always something else to learn, to discover, to deploy.

Evolve or die: this is the angle punter's mantra.


In part two of this series, which you can review here, I'll introduce you to Query Tool: what it is, where it lives, what it does and how it does it. And in part three, we'll work through a series of examples: micro angles which can be deployed as they are but, importantly, which are singular examples from rich seams whose nuggets are waiting to be extracted by the inquisitive Gold miner! 😉

Check it out here.


Punting Pointers: Naas Racecourse

For those of us to the east of the Irish Sea, we are having to currently having to cram on unfamiliar subjects if we have any aspirations of passing our daily wagering examinations. Today's test features a three hour 'paper', starting at 2pm, on Naas Racecourse. For those whose betting at the track has hitherto been blind, this post will attempt to at least partially sight!

Naas Course Constitution

The track is left-handed and has a straight five- and six-furlong piste. Mile and seven-furlong races begin in the chute furthest from the 'pin' on the image below, with ten-furlong and mile and a half races beginning in the straight just after the bend past the finish line.

Races at a mile and a quarter favour fast starters and/or inside draws as there is a dogleg almost immediately, whereafter the course gently arcs left-handed to about the six-furlong point. There is a further left turn with about half a mile to go meaning wider-drawn runners can have plenty of additional distance to travel; there is, however, a half a mile or so straight in which to make a challenge, so the key is not to get hung out wide on the turns.


Naas Draw / Pace

5f races

The five-furlong track has had a fairly pronounced low draw bias. That said, at the start of any new season it is important to look to see whether previous biases still hold; often, track maintenance undertaken in the close season can reduce, nullify or sometimes even reverse a previous bias. As things stand, then, the Naas five-furlong picture looks like this:

Those data are based on races at the track since 2009 with 10+ runners, and relate to 'actual draw' - that is, having removed non-runners from consideration (so, for instance, a horse drawn nine but with two non-runners inside him becomes 'actual draw' seven).

The Impact Value (IV, right hand column) for low-drawn horses is 1.48, which means they are nearly one and a half times as likely to win a race compared with random.

At geegeez.co.uk, we devised a metric called IV3 to smooth the curve on individual stall performance. It simply takes the average of a stall and its nearest neighbours: for instance, the IV3 for stall six comprises the sum of the IV for stalls five, six and seven divided by three. The IV3 graph for Naas 5f races looks like this:

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We can see a collection from stall four to ten at around 1.0, but higher draws are significantly unfavoured while berths one to three, especially stall one, have a notable edge.

But draw is not a one-dimensional consideration. Rather it needs to be considered in the context of the early pace horses are able to show. The below heat map illustrates the impact of both draw and run style and is clear about the importance of a very prominent early position, in terms of place percentages at least. Those held up, especially from a middle draw, have neither the pace nor the track position to compete generally.


1m2f races

As can be seen from the course image above, the ten-furlong range suggests it should strongly favour an inside draw, especially with pace to take advantage of that track position. The data support the logic:

We can clearly see the impact of a low draw on both win and place percentages, and with a strongly positive IV. The Actual over Expected (A/E) figure of 1.32 also implies the market hasn't fully factored low draw importance at this time.

Again, the IV3 chart is unequivocal:

Overlaying pace once more reveals that a low draw coupled with a 'led' or 'prominent' run style is a very big - and profitable - edge.


Naas Trainer Form

Overall Trainer Form

The top trainers in flat races at Naas in the five years from 2015 are as follows:

There are few surprises at the top of the overall list, with Aidan O'Brien lording over his peer group in terms of both strike rate and number of winners. From a punting perspective, the runners of Eddie Lynam and Andrew Oliver offer cause for hope.

Naas Handicap Trainer Form

The handicap picture looks different; here we have a number of trainers with solid win rates, numbers of wins and profit figures. Samples are smaller but still not inconsequential, with the likes of Aidan O'Brien, Jim Bolger, Ger Lyons and Jessica Harrington to the fore. These are four of the pre-eminent handlers in the land and they have all been profitable to back in Naas handicaps in recent years!

A word of caution with regards Joseph O'Brien. His seven winners have come at a cost of -27.75 points: clearly they can win but the market overestimates their chance.

Naas Early Season Trainer Form

Focusing only on the months or March and April at Naas, and we are in danger of slicing and dicing our way to statistical irrelevance (assuming we'd not already passed that point!)...

Again, the big guns of APOB, Ger Lyons, and Jessica Harrington are profitable to back. The place strike rates of Michael O'Callaghan, Tommy Stack, Ado McGuinness and Damian English all support their small numbers of winners and suggest they're worth keeping on side in March and April at Naas.

At the other end of the spectrum, Jim Bolger's strike rate in recent seasons has been a cautionary note, while Dermot Weld's horses also look overbet for all that they have a very solid place strike rate.

This article was researched using the Draw Analyser and Query Tool features within Geegeez Gold.


New and Improved: Draw / Pace Display

We're at the start of a busy period of development within Geegeez Gold just now, and an early part of this work is to bring a couple of rather clunky elements of the visuals into the 21st century.

Specifically, we've smoothed our draw and pace chart curves; and we've made the pace heat map a bit less 'blocky'.

There is also a new view on the Pace tab - and a very interesting one at that.

Gold users can now see which parts of the draw are favoured by the respective run styles, as well as which horses sit where against that draw / run style underlay. It's quite difficult to explain, so have a look at the short video below and see what you think.

Plenty more coming soon!


p.s. the user guide has been updated accordingly and you can download the latest version from your My Geegeez page.

Clock Watcher: Rise for National Anthem

Welcome to a new weekly feature, Clock Watcher, where we'll shine a light on a few horses that might be interesting to follow from a speed and/or sectional perspective. It is my hope that this column will also serve to introduce, embed and reinforce various concepts which may be unfamiliar at this stage.

Generally speaking, a run considered of sufficient merit to appear here will have two components: the horse will have recorded a time which is at least reasonably quick for the conditions; and the horse will have recorded a noteworthy upgrade on that performance.

The first component is fairly self-explanatory even if defining what is "at least reasonably quick" is highly subjective. Geegeez.co.uk doesn't currently produce its own speed ratings (and there is no plan for that to change at this stage), so for our purposes we will use Racing Post's Topspeed figures, which are published under license on this site.

The second component requires a bit more introduction. What is an 'upgrade', how does a horse achieve one, and how is this quantified?

What is an upgrade?

Track and field athletes run at their most efficient level - enabling them to produce their fastest times - when they travel at a constant speed. For instance, when Kenenisa Bekele broke the 5000m world record in 2004, a record which still stands today, his 1000m split times - or sectional times - were as follows:

12:37.35 (2:33.24, 2:32.23, 2:31.87, 2:30.59, 2:29.42)

Let's tabulate that:

A few months later, in the Olympic 5000m final, they covered the first 4 kilometres in 648.62 seconds, almost 41 seconds slower than the world record pace. Bekele, overwhelming favourite for gold, was readily out-sprinted and had to settle for silver, the winner recording a final time of 794.39 seconds, 37 seconds slower than the world record.

In a race where they crawled (relatively) and then sprinted, Bekele was unable to produce his best form. He could not run inefficiently to the same effect as his vanquisher, the Olympic 1500m champion Hicham El Guerrouj, whose superior kick facilitated his victory.

We know what is 'efficient' based on the body of similar historical races, and we call this par.

In simple terms, any deviation from efficiency - or par - whether fast early then fading, or slow early with a rapid finish, earns an upgrade. Thus, in this case, both the winner and second - as well, indeed, as the third through to sixth placed finishers - would have received upgrade figures.

An upgrade, then, is a recognition of the degree to which a horse raced inefficiently.

It should be noted that racing inefficiently will not necessarily prevent a horse, or an athlete, from winning. Indeed, El Guerrouj 'got the run of the race' back in 2004, that slow time suiting his questionable stamina but stronger kick. The primary objective is, after all, not to break records but to win the race.

What about par?

There is more detail in the User Guide around what may be new terms to some readers, and I'd encourage you to check that document (page 63 onwards in the current version, click here).

However, for the purposes of expediency, a quick line on par here. Par is the threshold against which all subsequent races over a course and distance are measured. From the User Guide,

Par is an assessment of the optimal energy distribution – based on relative time – between the sections of a race. It is not an average of all sectional times. Rather, it follows a fairly complex formula which uses an ‘nth percentile’ race as par. Further information can be found in Simon Rowlands’ excellent Sectional Timing Introduction report, available at this link. Indeed, that document is highly recommended for anyone keen to get a head start with the applications of sectional information.

So, in simple terms, par is a baseline, a means by which we may better understand the context of a performance.

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Let's look at some examples.


An obvious one...

We'll start with a sore thumb, a horse on everyone's radar regardless of whether via visuals, sectionals or form. The very well related Waldkonig made his debut in a run-of-the-mill Wolverhampton novice stakes for two-year-olds on 7th December. A Kingman half-brother to Arc winner Waldgeist, he was sent off 6/4 favourite over the extended mile trip.

In the end, he won by nine widening lengths; the data offer some interesting footnotes to that emphatic victory.


There is a lot going on in this image, so let's take it step by step. First up, note that I have selected 'Call Points' (a five section breakdown) top left and I have clicked the 'Show Chart' button, which then changes colour and displays 'Hide Chart', the action that would happen upon a further click. So those are my selected parameters. (I also have the data view selected from my My Geegeez page, check the User Guide for more on that).

Beneath the blue buttons is a line of five coloured rectangles. These are the Call Points sectionals for the race. That is, they relate to the race leader at five points during the race, specifically the six-furlong, four-furlong, three-furlong, two-furlong and finishing posts.

The colour of the rectangles indicates the relative speed of each section, on a cold/slow/blue to hot/fast/red scale. Thus, this race was even (green) early, slow (blue) in the middle, and fast (orange) late. The OMC (Opening, Midrace, Closing) view below captures this more succinctly and is a better place for newbies to start, due to there being fewer data points.

Getting back to the main image, and the main part of it, we see a chart. This chart is highly configurable but the image shows the default, which is the sectional percentage data, by furlong, for the winner - and with the black par line also displayed. Any/all runners can be added or removed to/from the chart by clicking their name underneath or using the 'toggle' button top left.

Next to the toggle button is a statement of how many races comprise the par calculations and, therefore, the degree of confidence in par. In this case - indeed in the vast majority of all-weather race cases - confidence is high. At this stage, confidence is more limited elsewhere while the body of data grows as more races are run over various courses and distances.

The chart reflects what the coloured rectangles are saying: that the leader went even-ish (slightly above par) early, slowed up notably in the middle of the race, before finishing very strongly - well above the black par line.

Beneath the chart is the full result table, which has a familiar look to it. I have clicked on the winner's finishing position (i.e. on the text that says '1st') to reveal his sectional data - coloured rectangles for Call Points (including split times, aggregates time, and sectional time as a percentage of overall time, i.e. sectional percentage), running lines (the horse's position in the field and distance behind the leader, or in front if the race leader) - and in-running comment.

The rightmost column in the result table is 'UP', and it contains the upgrade figure. In this example, Waldkonig was calculated as having an upgrade of 29 by our algorithm. Again, in terms of quantifying ability, this tells us little more than that, like his father, Waldkonig is able to quicken impressively off a steady pace.

Waldkonig was given a Topspeed rating of 47 for his time performance in the race. That is far from a standout rating and would not highlight the horse's effort as noteworthy, though of course the nine length winning margin would be missed by nobody. By applying the upgrade figure to a representation of the time performance we get closer to an understanding of the merit of the effort: clearly it takes more ability to quicken off a fast pace than a slow one, with the degree to which a horse quickens also worthy of note.

We've been playing with combining various numbers to produce some sort of 'composite' time/performance rating, though I must declare at this stage that I'm not 100% certain that adding upgrades to Topspeed is a sensible thing to do.

We are currently trying to establish whether it improves the predictive ability of the raw speed figure: they are calculated on different scales so it is probably not entirely sensible to simply add the two together.

Nevertheless, there is some indication in the work done to date that this somewhat contrived 'combo' number has merit. In the case of Waldkonig, his 47 gets an extra 29 for a 76 overall. That is a better reflection of his performance, though probably not of his ability given this was a debut on a track that was likely not ideal. In any case, what it tells us unequivocally is that, in a race where the pace scenario looks muddling, Waldkonig is capable of a searing turn of foot.


A (slightly) less obvious one...

At a slightly less 'could be anything' level, trainer David Brown rewarded his and connections' patience when National Anthem, off the track for 417 days since running poorly at the same venue, blasted home in a six-furlong novice event at Southwell. Brown is the horse's third trainer in three career starts spanning 821 days and a wind operation!

Sent off at 15/2, fifth favourite of six but not completely unfancied, his performance was very different in sectional terms to that of Waldkonig, as the image below illustrates:


Here we see from the running line that National Anthem jumped very alertly and maintained that advantage, albeit that it was diminishing in the final furlong. He was better than four lengths in front after a furlong and fully nine lengths clear with an eighth to go. Little wonder that he tired close home. Also little wonder that he's entered over five furlongs at the same track on Monday where it will be very interesting to see how he goes in a handicap off a mark of 75, if taking up his engagement.


Far more speculatively...

Meanwhile, down in the basement, a horse called Disruptor might pop up at a price some time soon. He ran on 30th December at Lingfield, finishing third, and as can be seen from the below he ran an almost polar opposite race to par - based on the five Call Point sections:


This lad has had a few goes - twelve, including one since, to be precise - and has showed much improved form when leading or racing prominently recently. Prior to his run on Monday, where his inexperienced (14 rides) jockey shot up in the air as the stalls opened and then got sandwiched between two no-hopers for most of a furlong, he'd run his three best races from the front.

If/when he can get a slightly softer advantage - note the undesirable red zone section from five to four in his running data above - he has a chance to see his race out more effectively, albeit very likely in low grade company and with a more experienced pilot on top.

That said, looking more closely at the draw (DR) column below, it is worth noting that he has been consistently fortunate with his stall position in recent starts.

[NB note also that, in 'Show Sectionals' mode, races without sectionals have blanks. Hovering over the running lines segment displays details of the performance, including comments, position, distance beaten and jockey].


That's all for this inaugural edition of Clock Watcher. I hope it has provided food for thought and that, over time, it will support your understanding of the new data we are beginning to provide and how you might best take advantage of it for yourself.

Until next time...


p.s. as of Wednesday 8th January, sectional data is now live for Gold subscribers on geegeez.co.uk. You will need to enable it from the Race Card Options section of your My Geegeez page. On that page, you will also find a link to the most recent version of the User Guide, in which there is a comprehensive outline of sectional timing and how it is published on this site.

The current coverage comprises Total Performance Data tracks, as it is from them that we license our data. We hope to be able to integrate both Ascot and RTV (UK) tracks in due course. To be clear, we have no in house sectional aggregation function. Rather, we license 3rd party data as a publisher and aim to add value in the visualisation of that data. I very much hope by mid-year we have a far more comprehensive provision in terms of track coverage.

Video: Sectional Data Overview

In today's video, you can catch a first glimpse of not one, but two, new things!

First off, want to know where geegeez.co.uk is now based? The introduction to this video reveals all - fancy Italian coffee shop included 🙂

More importantly (perhaps, what is more important than coffee?!), today I reveal for the first time how Gold subscribers will be able to interact with the sectional data we're soon to publish.

Please don't worry if you're new to sectional content, and/or if it doesn't really make sense at this stage. Over the next year and beyond I/we will be doing lots to bring certain sectional scenarios to life so that you not only understand what the data are saying, but also when they're saying something notable in the context of today's race.

I'm not a sectional expert; rather, I'm a publisher and a student of (old style) form looking to cut my teeth in this new time-based world. It will be an interesting journey for all of us, and it starts for you - if you want it to - with the video below...